Triple
T19694301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ylla |
E472912
|
entity |
| Predicate | hasTitleCharacter |
P5716
|
FINISHED |
| Object | Ylla |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ylla | Statement: [Ylla, hasTitleCharacter, Ylla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ylla Context triple: [Ylla, hasTitleCharacter, Ylla]
-
A.
Ylla
chosen
Ylla is a short story by Ray Bradbury, set on Mars and exploring the inner life and unfulfilled desires of a Martian woman.
-
B.
Loelva
Loelva is a river flowing through Norway’s scenic Loen valley, known for its glacial origins and striking turquoise waters.
-
C.
Nivala
Nivala is a small town and municipality in Northern Ostrobothnia, Finland, known for its rural character and agricultural surroundings.
-
D.
Velda
Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
-
E.
Vaala
Vaala is a municipality in northern Finland known for its lakeside landscapes and location along the Oulujoki river.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6421385e88190b22b12ab3d851dea |
completed | April 20, 2026, 3:11 p.m. |
Created at: April 10, 2026, 1:46 p.m.